This paper presents the recent activities of the Joint Working Group CIGRE C4/C6.35/CIRED. Specif... more This paper presents the recent activities of the Joint Working Group CIGRE C4/C6.35/CIRED. Specifically, the characteristics of Inverter Based Generation (IBG) is compared in detail with the characteristics of synchronous generators used in conventional power plants. In this context, the main differences are identified as: 1) the inertia; 2) the fault current provision; 3) the synchronization capability; and 4) the fixed internal voltage source. Those characteristics are provided by synchronous generators, but they are not easily provided by IBG. In order to overcome these differences grid code requirements for IBG need to be updated and thus, IBG units also have to provide ancillary services. Moreover, the paper presents the characteristics of IBG from the protection point of view. The internal and external protection of IBG is described in detail and examples are given.
The lack of sufficient labeled events and long training time limit the applicability of deep neur... more The lack of sufficient labeled events and long training time limit the applicability of deep neural network-based power system event identification using synchrophasor data. In this paper, we propose to leverage transfer learning technique to boost the reliability and reduce the required training time of neural classifier for power system event identification. We use the weights of a neural classifier trained on one transmission system as the initial parameters of another neural classifier for a different transmission system. Numerical tests with real-world synchrophasor data from the Eastern and Western Interconnections of the United States show that the proposed transfer learning approach is very effective in not only improving the training reliability but also reducing the training time.
25 Abstract The increasing penetration of Inverter Based Generation (IBG) over the last years has... more 25 Abstract The increasing penetration of Inverter Based Generation (IBG) over the last years has led to much effort on the development of IBG models for power system dynamic studies. CIGRE and CIRED established the joint working group CIGRE C4/C6.35/CIRED: “Modelling and dynamic performance of inverter based generation in power system transmission and distribution studies” with the aim of collecting the present best practices in the industry on modelling of IBG for power system dynamic studies, with the focus on photovoltaic systems. For that purpose, a questionnaire was distributed to utilities and system operators around the world. This paper summarizes some of the key findings about: 1) the studied power system; 2) the used IBG models (RMS and EMT models); and 3) the type of the performed studies. This survey supports utilities and system operators as well as research institutes and academia to benchmark their approach against the prevailing international industry practice.
2012 10th International Power & Energy Conference (IPEC), 2012
Inappropriate load models could cause discrepancies between the measured and simulated responses ... more Inappropriate load models could cause discrepancies between the measured and simulated responses in both the steady-state and transient state. Therefore, more accurate load models and their parameters need to be derived with the aid of measured data. Although more sophisticated measurement devices have been developed, the whole measured data such as for 30 seconds should not be used for deriving load model parameters, because the natural change in load structures regardless of voltage- and frequency-dependent load can deteriorate the accuracy of the derived voltage- and frequency-dependent load model parameters. In order to extract measured data that do not include the natural change in load structure, an automatic extraction method suitable for deriving load model parameters using a Fuzzy Inference System (FIS) is developed. The suitable data length can be specified using the correlation index between active power load and load bus voltage provided by the FIS. The measured data which are not used for the learning algorithm are used to validate the performance of the developed method.
This paper presents the recent activities of the Joint Working Group CIGRE C4/C6.35/CIRED. Specif... more This paper presents the recent activities of the Joint Working Group CIGRE C4/C6.35/CIRED. Specifically, the characteristics of Inverter Based Generation (IBG) is compared in detail with the characteristics of synchronous generators used in conventional power plants. In this context, the main differences are identified as: 1) the inertia; 2) the fault current provision; 3) the synchronization capability; and 4) the fixed internal voltage source. Those characteristics are provided by synchronous generators, but they are not easily provided by IBG. In order to overcome these differences grid code requirements for IBG need to be updated and thus, IBG units also have to provide ancillary services. Moreover, the paper presents the characteristics of IBG from the protection point of view. The internal and external protection of IBG is described in detail and examples are given.
The lack of sufficient labeled events and long training time limit the applicability of deep neur... more The lack of sufficient labeled events and long training time limit the applicability of deep neural network-based power system event identification using synchrophasor data. In this paper, we propose to leverage transfer learning technique to boost the reliability and reduce the required training time of neural classifier for power system event identification. We use the weights of a neural classifier trained on one transmission system as the initial parameters of another neural classifier for a different transmission system. Numerical tests with real-world synchrophasor data from the Eastern and Western Interconnections of the United States show that the proposed transfer learning approach is very effective in not only improving the training reliability but also reducing the training time.
25 Abstract The increasing penetration of Inverter Based Generation (IBG) over the last years has... more 25 Abstract The increasing penetration of Inverter Based Generation (IBG) over the last years has led to much effort on the development of IBG models for power system dynamic studies. CIGRE and CIRED established the joint working group CIGRE C4/C6.35/CIRED: “Modelling and dynamic performance of inverter based generation in power system transmission and distribution studies” with the aim of collecting the present best practices in the industry on modelling of IBG for power system dynamic studies, with the focus on photovoltaic systems. For that purpose, a questionnaire was distributed to utilities and system operators around the world. This paper summarizes some of the key findings about: 1) the studied power system; 2) the used IBG models (RMS and EMT models); and 3) the type of the performed studies. This survey supports utilities and system operators as well as research institutes and academia to benchmark their approach against the prevailing international industry practice.
2012 10th International Power & Energy Conference (IPEC), 2012
Inappropriate load models could cause discrepancies between the measured and simulated responses ... more Inappropriate load models could cause discrepancies between the measured and simulated responses in both the steady-state and transient state. Therefore, more accurate load models and their parameters need to be derived with the aid of measured data. Although more sophisticated measurement devices have been developed, the whole measured data such as for 30 seconds should not be used for deriving load model parameters, because the natural change in load structures regardless of voltage- and frequency-dependent load can deteriorate the accuracy of the derived voltage- and frequency-dependent load model parameters. In order to extract measured data that do not include the natural change in load structure, an automatic extraction method suitable for deriving load model parameters using a Fuzzy Inference System (FIS) is developed. The suitable data length can be specified using the correlation index between active power load and load bus voltage provided by the FIS. The measured data which are not used for the learning algorithm are used to validate the performance of the developed method.
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Papers by Koji Yamashita